Submodular Function Maximization in Parallel via the Multilinear Relaxation

@inproceedings{Chekuri2019SubmodularFM,
  title={Submodular Function Maximization in Parallel via the Multilinear Relaxation},
  author={Chandra Chekuri and Kent Quanrud},
  booktitle={SODA},
  year={2019}
}
Balkanski and Singer [5] recently initiated the study of adaptivity (or parallelism) for constrained submodular function maximization, and studied the setting of a cardinality constraint. Very recent improvements for this problem by Balkanski, Rubinstein, and Singer [6] and Ene and Nguyen [21] resulted in a near-optimal $(1-1/e-\epsilon)$-approximation in $O(\log n/\epsilon^2)$ rounds of adaptivity. Partly motivated by the goal of extending these results to more general constraints, we describe… CONTINUE READING
Tweets
This paper has been referenced on Twitter 5 times. VIEW TWEETS